PID tuning rules - Open Loop Tuning / Closed Loop tuning

Open Loop Tuning Rules

Process Reaction Curve: The process reaction curve is an approximate model of the process, assuming the process behaves as a first order plus deadtime system. The process reaction curve is identified by doing an open loop step test of the process and identifying process model parameters. · Put the controller in manual mode · Wait until the process value (Y) is stable and not changing · Step the output of the PID controller - The step must be big enough to see a significant change in the process value. A rule of thumb is the signal to noise ratio should be greater than 5. · Collect data and plot as shown below. · Repeat making the step in the opposite direction. · K = the process gain K = Change in Process Value/ Change in manipulated value

Open Loop Tuning Most tuning rules have a suggested range of applicability based on the ratio of a/t. Check to make sure the tuning rule is applicable before using. · These tuning rules do not work for integrating processes. (level control for example) · Make sure the PID equation your DCS uses is consistent with the standard form. If it is not transform the tuning constants to the appropriate form for your DCS.

Some DCS systems use scaled values in the PID equation. If so tuning constants based on process engineering units may be incorrect. · Steps should be made around the expected operating point. · Steps should be made in both directions. Dynamics are very often directionally dependent. · If the system is nonlinear steps should be made around the most sensitive (highest K value) part of the expected operating range. If this is not done it is possible for the controller to become oscillatory or even unstable when controlling in this region. · Different tuning rules are based on different performance criteria. Select the one that most closely represents your desired response · Remember these tuning rules are based on approximate models and thus should be a starting point in the tuning process. · Beware of derivative action Ø Derivative action is very sensitive to process noise. Ø If setpoint changes will be made to the process the controller should be doing derivative action on measurement not error. If the derivative action is on error the output of the controller will spike when setpoint changes are made. Ø Derivative action is best suited for processes with significant deadtime and lag.

Closed Loop Tuning Rules Ziegler-Nichols closed loop tuning is based on stability margins. To identify process parameters:

  1. Turn off both integral and derivative action in the controller. This can usually be accomplished by putting zeros in the integral and derivative tuning parameters.
  2. Set the proportional gain (Kc) to a small value.
  3. Put the controller in Auto mode.
  4. Make a small step in the controller setpoint.
  5. Observe the process response.
  6. If the controller does not continually cycle (stability limit), increase the controller gain (Kc) and repeat from step 4.
  7. Once the controller continually oscillates, the controller gain is the ultimate gain Kcu.
  8. Measure the period of the cycle and this is the ultimate period Pu.

Things to watch out for (Closed Loop Tuning): · Many processes should not be tuned using stability limit tuning rules. To get the process parameters the system has to be brought to the brink of instability. This is very often undesirable and sometimes even dangerous. · Recognize that with P-only control there will be steady state offset. · Do not let the manipulated variable saturate high or low. · Use the smallest controller gain that gives marginal stability as the ultimate gain. · Make sure the PID equation your DCS uses is consistent with the standard form. If it is not transform the tuning constants to the appropriate form for your DCS.

Some DCS systems use scaled values in the PID equation. If so tuning constants based on process engineering units may be incorrect. · Steps should be made around the expected operating point. · Steps should be made in both directions. Dynamics are very often directionally dependent. · If the system is nonlinear steps should be made around the most sensitive (highest process gain value) part of the expected operating range. If this is not done it is possible for the controller to become oscillatory or even unstable when controlling in this region. · Cycle won’t always be symmetric due to different dynamics for process steps up Vs down. · Tuning rules should be a starting point in the tuning process. · Beware of derivative action Ø Derivative action is very sensitive to process noise. Ø If setpoint changes will be made to the process the controller should be doing derivative action on measurement not error. If the derivative action is on error the output of the controller will spike when setpoint changes are made. Ø Derivative action is best suited for processes with significant deadtime and lag.